Although there has been extensive research on the adverse impacts of perceived discrimination on health, it remains unclear how perceived discrimination gets under the skin. This paper develops a comprehensive structural equation model (SEM) by incorporating both the direct effects of perceived discrimination on self-rated health (SRH), a powerful predictor for many health outcomes, and the indirect effects of perceived discrimination on SRH through health care system distrust, neighborhood social capital, and health behaviors and health conditions. Applying SEM to 9,880 adults (aged between 18 and 100) in the 2008 Southeastern Pennsylvania Household Health Survey, we not only confirmed the positive and direct association between discrimination and poor or fair SRH, but also verified two underlying mechanisms: 1) perceived discrimination is associated with lower neighborhood social capital, which further contributes to poor or fair SRH; and 2) perceived discrimination is related to risky behaviors (e.g., reduced physical activity and sleep quality, and intensified smoking) that lead to worse health conditions, and then result in poor or fair SRH. Moreover, we found that perceived discrimination is negatively associated with health care system distrust, but did not find a significant relationship between distrust and poor or fair SRH.
We conducted a meta‐analysis of food and agricultural demand elasticities for China, and used the results to derive estimates of income, own‐price, and cross‐price elasticities of demand that can be used in models of food and agricultural markets. Consistent with expectations, we find that income elasticities of demand for many food products decline as per capita income increases. The declines are relatively large for alcohol and tobacco, and smaller for livestock products. Contrary to expectations, own‐price elasticities for some products become more price‐elastic as per capita income increases. One explanation may be that economic development brings with it improvements in food supply chains that provide people more choices with respect to food products than those traditionally consumed in rural villages, leading to greater substitution possibilities and more price‐elastic demands. Estimates for 2011 of income and own‐price demand elasticities are generally reasonable, whereas deriving reliable estimates of cross‐price elasticities is difficult. The estimates suggest that China's meat and dairy demands, and in turn livestock feed demands, will continue growing strongly. Policy‐makers should continue to monitor the evolution of demand for these products with an eye toward ensuring food security, particularly given the sheer size of the population and relatively tight domestic food supply situation in China.
Neighborhood food environment factors, such as food desert status, were associated with obesity status even after we controlled for home food environment factors.
Background The older population size has increased substantially, and a considerable proportion of older adults are cigarette smokers. Quitting smoking is associated with reduced health risk. This review is among the first to quantitatively assess the relative efficacy of types of cessation interventions for smokers aged ≥ 50 years. Methods We conducted searches of the Cochrane Library, Embase, MEDLINE, and PsycINFO to identify smoking cessation studies on adults aged ≥ 50 years. Twenty-nine randomized clinical trials met the inclusion criteria. Three main types of interventions were identified. We analyzed relative cessation rates or Risk Ratios (RRs) between the type of intervention groups and the control group by fixed- and random-effects meta-analyses at the study level. We conducted a weighted least squares meta-regression of cessation rates on trial and sample characteristics to determine sources of outcome heterogeneity. Results Fixed-effects analysis showed significant treatment effects for pharmacological (RR=3.18, 95% CI: 1.89–5.36), non-pharmacological (RR=1.80, 95% CI: 1.67–1.94), and multimodal interventions (RR=1.61, 95% CI: 1.41–1.84) compared with control group. Estimations based on meta-regression suggested that pharmacological intervention (mean point prevalence abstinence rate (PPA) = 26.10%, CI: 15.20–37.00) resembled non-pharmacological (27.97%, CI: 24.00–31.94), and multimodal interventions (36.64%, CI: 31.66–41.62); and non-pharmacological and multimodal interventions had higher PPAs than the control group (18.80%, CI: 14.48–23.12), after adjusting for a number of trial and sample characteristics. Conclusions A small number of smoking cessation studies examined smokers aged ≥ 50 years. Additional research is recommended to determine smoking cessation efficacy for diverse older population groups (e.g., ethnic minorities).
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